Example

In [1]:

import geopandas as gpd
import geodatasets as gds
nyc_dataset_path = gds.get_path('nybb')
nyc = gpd.read_file(nyc_dataset_path)

import geopandas as gpd import geodatasets as gds nyc_dataset_path = gds.get_path('nybb') nyc = gpd.read_file(nyc_dataset_path)

Downloading file 'nybb_16a.zip' from 'https://www.nyc.gov/assets/planning/download/zip/data-maps/open-data/nybb_16a.zip' to '/home/runner/.cache/geodatasets'.

Extracting 'nybb_16a/nybb.shp' from '/home/runner/.cache/geodatasets/nybb_16a.zip' to '/home/runner/.cache/geodatasets/nybb_16a.zip.unzip'

Extracting 'nybb_16a/nybb.shx' from '/home/runner/.cache/geodatasets/nybb_16a.zip' to '/home/runner/.cache/geodatasets/nybb_16a.zip.unzip'

Extracting 'nybb_16a/nybb.dbf' from '/home/runner/.cache/geodatasets/nybb_16a.zip' to '/home/runner/.cache/geodatasets/nybb_16a.zip.unzip'

Extracting 'nybb_16a/nybb.prj' from '/home/runner/.cache/geodatasets/nybb_16a.zip' to '/home/runner/.cache/geodatasets/nybb_16a.zip.unzip'

To render HTML content in a Jupyter notebook, you can use the IPython.display module.

In [2]:

from IPython.display import display, HTML, IFrame

nyc.explore()

from IPython.display import display, HTML, IFrame nyc.explore()

Out[2]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [3]:

from plotly import express as px

px.choropleth_mapbox(nyc, locations='BoroCode', color='BoroName')

from plotly import express as px px.choropleth_mapbox(nyc, locations='BoroCode', color='BoroName')

In [4]:

display(HTML(px.scatter(nyc, x='Shape_Leng', y='Shape_Area').to_html()))

display(HTML(px.scatter(nyc, x='Shape_Leng', y='Shape_Area').to_html()))